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Record W4387381490 · doi:10.1142/s0219525923400040

STRUCTURAL PROPERTIES OF CORE–PERIPHERY COMMUNITIES

2023· article· en· W4387381490 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Complex Systems · 2023
Typearticle
Languageen
FieldMaterials Science
TopicSolid-state spectroscopy and crystallography
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCore (optical fiber)Economic geographySocial network analysisNetwork structureComputer scienceEconomicsSociologyTheoretical computer scienceSocial capitalSocial scienceTelecommunications

Abstract

fetched live from OpenAlex

Empirical studies have consistently demonstrated the presence of a core–periphery structure within social network communities. Nevertheless, a formal model and comprehensive analysis to fully understand the structural characteristics of these communities are still lacking. This paper seeks to characterize these properties, focusing on agents’ interconnections and their allocation of rates. Employing a game-theoretic approach, our analysis unveils several novel insights. First, we show that periphery agents not only follow core agents but also other periphery agents who share similar primary interests. Second, our results illuminate the emergence of core–periphery communities, revealing the conditions under which they form, and how they form.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.313
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it